Solar photocatalytic membranes: an experimental and artificial neural network modeling approach for niflumic acid degradation
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/1822/80751 |
Resumo: | The presence of contaminants of emerging concern (CEC), such as pharmaceuticals, in water sources is one of the main concerns nowadays due to their hazardous properties causing severe effects on human health and ecosystem biodiversity. Niflumic acid (NFA) is a widely used anti-inflammatory drug, and it is known for its non-biodegradability and resistance to chemical and biological degradation processes. In this work, a 10 wt.% TiO<sub>2</sub>/PVDF–TrFE nanocomposite membrane (NCM) was prepared by the solvent casting technique, fully characterized, and implemented on an up-scaled photocatalytic membrane reactor (PMR). The photocatalytic activity of the NCM was evaluated on NFA degradation under different experimental conditions, including NFA concentration, pH of the media, irradiation time and intensity. The NCM demonstrated a remarkable photocatalytic efficiency on NFA degradation, as efficiency of 91% was achieved after 6 h under solar irradiation at neutral pH. The NCM proved effective in long-term use, with maximum efficiency losses of 7%. An artificial neural network (ANN) model was designed to model NFA’s photocatalytic degradation behavior, demonstrating a good agreement between experimental and predicted data, with an R<sup>2</sup> of 0.98. The relative significance of each experimental condition was evaluated, and the irradiation time proved to be the most significant parameter affecting the NFA degradation efficiency. The designed ANN model provides a reliable framework l for modeling the photocatalytic activity of TiO<sub>2</sub>/PVDF-TrFE and related NCM. |
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Solar photocatalytic membranes: an experimental and artificial neural network modeling approach for niflumic acid degradationartificial neural networkmodellingnanocomposite membraneniflumic acidphotocatalysisphotocatalytic membrane reactorScience & TechnologyThe presence of contaminants of emerging concern (CEC), such as pharmaceuticals, in water sources is one of the main concerns nowadays due to their hazardous properties causing severe effects on human health and ecosystem biodiversity. Niflumic acid (NFA) is a widely used anti-inflammatory drug, and it is known for its non-biodegradability and resistance to chemical and biological degradation processes. In this work, a 10 wt.% TiO<sub>2</sub>/PVDF–TrFE nanocomposite membrane (NCM) was prepared by the solvent casting technique, fully characterized, and implemented on an up-scaled photocatalytic membrane reactor (PMR). The photocatalytic activity of the NCM was evaluated on NFA degradation under different experimental conditions, including NFA concentration, pH of the media, irradiation time and intensity. The NCM demonstrated a remarkable photocatalytic efficiency on NFA degradation, as efficiency of 91% was achieved after 6 h under solar irradiation at neutral pH. The NCM proved effective in long-term use, with maximum efficiency losses of 7%. An artificial neural network (ANN) model was designed to model NFA’s photocatalytic degradation behavior, demonstrating a good agreement between experimental and predicted data, with an R<sup>2</sup> of 0.98. The relative significance of each experimental condition was evaluated, and the irradiation time proved to be the most significant parameter affecting the NFA degradation efficiency. The designed ANN model provides a reliable framework l for modeling the photocatalytic activity of TiO<sub>2</sub>/PVDF-TrFE and related NCM.This research was funded by Fundação para a Ciência e Tecnologia (FCT) grant numbers SFRH/BD/122373/2016 and COVID/BD/151786/2021 and contract 2020.02802.CEECIND.This work was supported by Solar Equipment Development Unit (UDES) and Portuguese Foundation for Science and Technology (FCT) in the framework of the Strategic Projects UID/FIS/04650/20132019 and UID/QUI/50006/2019 and project PTDC/FIS-MAC/28157/2017. H. Salazar and P. M. Martins thank the FCT for the grants SFRH/BD/122373/2016 and COVID/BD/151786/2021, and the contract 2020.02802.CEECIND. Financial support from the Basque Government Industry and Education Departments under the ELKARTEK program is also acknowledged.Multidisciplinary Digital Publishing InstituteUniversidade do MinhoAoudjit, LamineSalazar, HugoZioui, DjamilaSebti, AichaMartins, Pedro Manuel AbreuLanceros-Méndez, S.2022-08-302022-08-30T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/80751engAoudjit, L.; Salazar, H.; Zioui, D.; Sebti, A.; Martins, P.M.; Lanceros-Méndez, S. Solar Photocatalytic Membranes: An Experimental and Artificial Neural Network Modeling Approach for Niflumic Acid Degradation. Membranes 2022, 12, 849. https://doi.org/10.3390/membranes120908492077-037510.3390/membranes12090849https://www.mdpi.com/2077-0375/12/9/849info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:49:14Zoai:repositorium.sdum.uminho.pt:1822/80751Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:47:40.123278Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Solar photocatalytic membranes: an experimental and artificial neural network modeling approach for niflumic acid degradation |
title |
Solar photocatalytic membranes: an experimental and artificial neural network modeling approach for niflumic acid degradation |
spellingShingle |
Solar photocatalytic membranes: an experimental and artificial neural network modeling approach for niflumic acid degradation Aoudjit, Lamine artificial neural network modelling nanocomposite membrane niflumic acid photocatalysis photocatalytic membrane reactor Science & Technology |
title_short |
Solar photocatalytic membranes: an experimental and artificial neural network modeling approach for niflumic acid degradation |
title_full |
Solar photocatalytic membranes: an experimental and artificial neural network modeling approach for niflumic acid degradation |
title_fullStr |
Solar photocatalytic membranes: an experimental and artificial neural network modeling approach for niflumic acid degradation |
title_full_unstemmed |
Solar photocatalytic membranes: an experimental and artificial neural network modeling approach for niflumic acid degradation |
title_sort |
Solar photocatalytic membranes: an experimental and artificial neural network modeling approach for niflumic acid degradation |
author |
Aoudjit, Lamine |
author_facet |
Aoudjit, Lamine Salazar, Hugo Zioui, Djamila Sebti, Aicha Martins, Pedro Manuel Abreu Lanceros-Méndez, S. |
author_role |
author |
author2 |
Salazar, Hugo Zioui, Djamila Sebti, Aicha Martins, Pedro Manuel Abreu Lanceros-Méndez, S. |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Aoudjit, Lamine Salazar, Hugo Zioui, Djamila Sebti, Aicha Martins, Pedro Manuel Abreu Lanceros-Méndez, S. |
dc.subject.por.fl_str_mv |
artificial neural network modelling nanocomposite membrane niflumic acid photocatalysis photocatalytic membrane reactor Science & Technology |
topic |
artificial neural network modelling nanocomposite membrane niflumic acid photocatalysis photocatalytic membrane reactor Science & Technology |
description |
The presence of contaminants of emerging concern (CEC), such as pharmaceuticals, in water sources is one of the main concerns nowadays due to their hazardous properties causing severe effects on human health and ecosystem biodiversity. Niflumic acid (NFA) is a widely used anti-inflammatory drug, and it is known for its non-biodegradability and resistance to chemical and biological degradation processes. In this work, a 10 wt.% TiO<sub>2</sub>/PVDF–TrFE nanocomposite membrane (NCM) was prepared by the solvent casting technique, fully characterized, and implemented on an up-scaled photocatalytic membrane reactor (PMR). The photocatalytic activity of the NCM was evaluated on NFA degradation under different experimental conditions, including NFA concentration, pH of the media, irradiation time and intensity. The NCM demonstrated a remarkable photocatalytic efficiency on NFA degradation, as efficiency of 91% was achieved after 6 h under solar irradiation at neutral pH. The NCM proved effective in long-term use, with maximum efficiency losses of 7%. An artificial neural network (ANN) model was designed to model NFA’s photocatalytic degradation behavior, demonstrating a good agreement between experimental and predicted data, with an R<sup>2</sup> of 0.98. The relative significance of each experimental condition was evaluated, and the irradiation time proved to be the most significant parameter affecting the NFA degradation efficiency. The designed ANN model provides a reliable framework l for modeling the photocatalytic activity of TiO<sub>2</sub>/PVDF-TrFE and related NCM. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-08-30 2022-08-30T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/1822/80751 |
url |
https://hdl.handle.net/1822/80751 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Aoudjit, L.; Salazar, H.; Zioui, D.; Sebti, A.; Martins, P.M.; Lanceros-Méndez, S. Solar Photocatalytic Membranes: An Experimental and Artificial Neural Network Modeling Approach for Niflumic Acid Degradation. Membranes 2022, 12, 849. https://doi.org/10.3390/membranes12090849 2077-0375 10.3390/membranes12090849 https://www.mdpi.com/2077-0375/12/9/849 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Multidisciplinary Digital Publishing Institute |
publisher.none.fl_str_mv |
Multidisciplinary Digital Publishing Institute |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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